mpw-007 / RRM RRAM mask

the RRM shapes of all of mpw-007

40 of 40 dies rendered, 34 with nothing on this mask.

76,842 shapes in total, each die at 0.125 µm per pixel.

result.json · job.json · reticle overview PNG

1234567
A A1 A2 A3 A4 A5 A6
B B1 B2 B3 B4 B5 B6 B7
C C1 C2 C3 C4 C6
C6 slot-018 tile
soomrv
(empty)
C7
D D1 D2 D3 D4 D5 D6 D7
E E1 E2 E3 E4 E5 E6 E7
F F1 F2 F3 F4 F5 F6 F7

Downloading the full-resolution image

The stitched reticle is 53,432×65,056 pixels — 3.48 gigapixels. The file itself is small, but decoding it needs about 3.5 GB of memory however small the file is, and most viewers refuse it outright. So it is also published as 42 tiles of about 7576×10776 px (4.4 MB in total, largest 121.9 kB), cut in the gaps between dies so that every tile holds whole projects and none is split.

To put the full-resolution PNG back together from them, byte for byte, with nothing installed but Python itself:

python3 reconstruct_reticle.py

Run it in a directory holding the tiles and mpw-007_RRM_tiles.json and it finds them itself, checks every tile against its checksum as it reads it, and checks the finished file against the manifest. It works because the tiles and the full image are written with PNG's Up filter, which never looks at the pixel to its left — so a row of tiles' scanlines laid end to end is the full image's scanline, and rebuilding moves bytes rather than doing pixel arithmetic.

Whole-reticle files

FileSizeMD5SHA-1SHA-256
mpw-007_RRM_reticle.png
the stitched reticle, full resolution
3.5 MB 4d30f21ac79fb058e7c07590856ee21d5404a5c282a2ae785ea997253ddcb9b93cf7ed23 55c4f0369309db57c2c81e9648b4225dc1e73798540545492746dacbfd7d2f99
mpw-007_RRM_reticle_overview.png
the same image scaled to fit 4096 px
14.7 kB 1113b74e4844936e60f9c52a37eac6e940c85e1a12e90e7d6ea4c559cb87a9a9ce275afc e2863ff1eae05bd767fc1443609249804aa23f3abaccd052abd75a74f24cb3b9
mpw-007_RRM_tiles.json
where every tile belongs, and its checksum
13.5 kB 9c2610e1f0d4894412bb3a1a6d6c8babb566cc12883e713cfdb2e7c303413c9d42406e93 085f69e560b601c6f1fd59b0d23a44bf00486c348355bffc42eea1a3c9aa84e9
reconstruct_reticle.py
rebuilds the reticle from the tiles, standard library only
11.9 kB 4406f1f3db8a4a85756610b7c432c47a294714566ceb084187594ced0020f9260faac32a d2e72bf4b2541f1a8acb11eb758917c5b5fa080b41b3a7118487c03f8af2a769

Every file in this directory is listed in MD5SUMS · SHA1SUMS · SHA256SUMS, in the format the standard tools read:

sha256sum -c SHA256SUMS

The 42 tiles

FrameProjectPixelsPositionSizeSHA-256
A1 tinytapeout 7576×107760, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A2 zero_to_asic_course_group_submission_mpw7 7576×107767576, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A3 microwatt_mpw7 7576×1077615152, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A4 yonga-can_controller 7576×1077622728, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A5 rocketalpha 7576×1077630304, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A6 riscduino-dcore_d3_3 7576×1077637880, 0 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 riscduino-qcore_q2_3 7576×107760, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B2 riscduino-score-s4-3 7576×107767576, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B3 nanofabrication_project_using_openfasoc 7576×1077615152, 10776 103.2 kB8ac025debd2a65527773b65e2c6394340cc7172b2ca8d3acd2f301c59e88ff11
B4 sramtestvehicleg3 7576×1077622728, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B5 analog_frontend_for_particle_detection_resubm 7576×1077630304, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B6 isa_16-bit_microprocessor 7576×1077637880, 10776 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
B7 reram_crossbar 7976×1077645456, 10776 111.1 kBbc51612382e3c105501152b2d0b17d3c96f6fdf4afb65827f67e1a40abcd92e8
C1 trainable-nn 7576×107760, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C2 10b_adc_and_analog_support_-_update 7576×107767576, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C3 bitcoin_mining_asics 7576×1077615152, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C4 yonga-mcu 7576×1077622728, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 soomrv 7576×1077637880, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C7 marmot_risc-v_asic_for_motor_control 7976×1077645456, 21552 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
D1 mixed_signal_circuits-jun13 7576×107760, 32328 102.9 kB638bd009c671ec0eb0db4253ca7e2722000a7fc4df1bcc0b82f06083ae8be9f8
D2 fpga_programming_management_unit 7576×107767576, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D3 warp-v 7576×1077615152, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D4 leaf__mpw7_ 7576×1077622728, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D5 in_memory_computing_sram 7576×1077630304, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D6 rng_based_on_a_figaro_oscillator 7576×1077637880, 32328 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
D7 reram-controller-mpw7_v2 7976×1077645456, 32328 121.9 kB79515801b966af7ec4d23f00339882f4c3594633bba5812e4cf0d90a78c863f6
E1 enhanced_chaotic_oscillator_design 7576×107760, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E2 in_memory_computing_rram 7576×107767576, 43104 103.6 kB8a72ed5482eb3026233db4ed0167eb6bf1d18b6280616e05867f3c922cbd2a80
E3 rram_imc_v2_flat 7576×1077615152, 43104 103.6 kB8a72ed5482eb3026233db4ed0167eb6bf1d18b6280616e05867f3c922cbd2a80
E4 topmetalse-dps 7576×1077622728, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E5 chaos_automaton 7576×1077630304, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E6 hehecore_resubmission 7576×1077637880, 43104 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
E7 waveform_generator 7976×1077645456, 43104 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
F1 rift2core 7576×111760, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F2 rift2go_2300 7576×111767576, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F3 sloci_resubmission 7576×1117615152, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F4 systolic_array_matrix_multiplier 7576×1117622728, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F5 crypto_aes128 7576×1117630304, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F6 graphics_controller 7576×1117637880, 53880 106.5 kBe0080bf93247638505ac8cbca0ff50d5edfb396bd4199cc28c584a06ab77ed95
F7 prga-test 7976×1117645456, 53880 110.7 kB4819853e853378d6bf252c7d9d89c4caedfec9d3b73e01c973cd666bce8783c6

Position is the tile's top-left corner in the full-resolution image. MD5 and SHA-1 for the same files are in the checksum files linked above.

About RRM on mpw-007

Resolved: reticle 5CS8016AC, run mpw-007, mask RRM

Mask layer
RRM — RRAM mask
Drawn layer
201:20
Detail
the RRAM-stack mask (r1c) of the sky130B RRAM tier between met1 and met2. One drawn layer r1c = GDS 201/20 (open_pdks names it RERAM, short alias 'rr' -> 'rr' + M) defines all three physical films: rr1_bot_electrode, rr1_oxide, rr1_top_electrode. Only on the later sets 5CS8016AC/17AC/18AC. sky130A designs draw no 201/20, so those slots render empty
Also
sky130B RRAM tier (met1-met2); drawn layer r1c = GDS 201/20
Used in SKY130
no

mpw-007 — SKY130 MPW-7

Reticle set
5CS8016AC
Run date
2022-07-08
Submissions closed
2022-09-12
Projects
106
Identification
inferred — Sequence after 5CS8014AC=MPW-6 (8018 is the re-made MPW-4 set); packing list 2026-08-25
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-7 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-007/foundry

These are renders of the drawn shapes that go on each photomask, taken from the layouts the shuttle's projects taped out — they are not photomask artwork: reticle pitch, the 4x reduction, mirroring and the frame features the fab adds are not modelled. An empty image is a real result; several mask layers are used by no project on a given shuttle. Each die's source layout is named in result.json and lives in the public shuttle repositories under foss-eda-tools.googlesource.com, so every image here can be traced back to the tape-out it came from. Generated with sky130-mask-decoder.